Mobile wireless sensor network

Résumé

A mobile wireless sensor network (MWSN) can simply be defined as a wireless sensor network (WSN) in which the sensor nodes are mobile. MWSNs are a smaller, emerging field of research in contrast to their well-established predecessor. MWSNs are much more versatile than static sensor networks as they can be deployed in any scenario and cope with rapid topology changes. However, many of their applications are similar, such as environment monitoring or surveillance. Commonly, the nodes consist of a radio transceiver and a microcontroller powered by a battery, as well as some kind of sensor for detecting light, heat, humidity, temperature, etc. Challenges Broadly speaking, there are two sets of challenges in MWSNs; hardware and environment. The main hardware constraints are limited battery power and low cost requirements. The limited power means that it's important for the nodes to be energy efficient. Price limitations often demand low complexity algorithms for simpler microcontr

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https://en.wikipedia.org/wiki/Mobile_wireless_sensor_network

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Distributed Sensor Data Models and Their Impact on Energy Consumption of Wireless Sensor Networks

Urs Hunkeler

EPFL2013

Chargement

Wireless sensors are small devices that are able to gather, process and deliver information from a physical environment to an external system. By doing so, they open new applications in different domains, such as healthcare, traffc control, defense and agriculture. The integration of Wireless Sensor Networks (WSN) with Business Applications (BA) raises technical and security related challenges. Existing approaches target technical issues such as interoperability between WSN and BAs or heterogeneity of acquired sensor data. In this work, we start by performing an analysis of the risks that such an integration of WSNs with BAs may present using the NIST SP 800-30 recommendations. We then introduce and analyze an effcient security scheme that does not use complex operations and guarantees end-to-end confidentiality of sensor data. Finally, we provide an in silico proof-of-concept and validate it using a real WSN co-developed with Cisco Systems France.

2008

Chargement

The purpose of this research has a background in the market for Internet of Things (IoT)devices and wireless sensor networks. The Market Forecast predicts the connection of a trillion"things" by 2025. The global smart sensor market size trend grows from USD 36.6 billion in2020 to USD 87.6 billion by 2025, at a CAGR of 19.0 %. The energy harvesting systems market is worth USD 440.39 million in 2019 with a forecast to reach USD 817.2 million by 2025, at a CAGR of 10.91 %, over the forecast period(2020-2025). In this scenario, to power a trillion node IoT infrastructure would require trillions of batteries which poses maintenance problems and related non-negligible management costs. Indeed, for every trillion nodes installed, 274million batteries would need to be replaced every day, even in the best-case scenario where it is possible to assume that batteries reach their 10-year life expectancy. In this context, this thesis aims to show innovative systems, strategies, techniques, and circuits for powering low-maintenance,energy-autonomous, and battery-free devices. The principal intention is to contribute to the research effort of Wireless Sensor Node (WSN) that is sustainable and needs minimal or no maintenance. More, in particular, it shows how RF wireless power transfer (WPT) with its pervasiveness is, in some practical use cases, a very convenient way to remotely supply wireless nodes, especially when installed in locations difficult to reach. In terms of systems and circuits, this work presents a state-of-the-art, ultra-low-power 2.5µW highly integrated mixed-signal system on chip (SoC), for multi-source energy harvesting(EH) and RF wireless power transfer. The SoC implements an architecture that integrates a high-performance nano-power management, a wide-bandwidth (350 MHz - 2.4 GHz)RF to DCconverter, with low power sensitivity (-22 dBm at 868 MHz) and maximum Power Conversion Efficiency (PCE) (55% at the minimum input power). For the PCE optimization over several operating conditions, the system integrates an innovative ultra-low-power Maximum Power Point Tracking (MMPT) system. The IC integrates an accurate Amplitude-Shift-Keyingand Frequency-Shift-Keying (ASK/FSK) demodulator and digital circuitry to allow over the air configuration of the SoC while powered by an RF power source. The integration of an ultra-low-power asynchronous finite state machine and a programmable logic allow the implementation of several features that render the system versatile and able to deal with different energy sources and use cases with minimal external components. The SoC is fabricated in a0.13µmCMOS technology in a core area of 2.7mm2.vAs for the strategies and techniques, this thesis discusses several innovative methods that aim both to postpone the maintenance interventions of battery-powered nodes over time, and when possible, to cancel the maintenance of the nodes by eliminating the battery. Therefore, it is shown how to power a WSN through energy harvesting and RF wireless power transfer by discussing system architectures and experimental results in detail. One of the presented strategies highlights that the main issue to solve in battery-suppliedWSN is how to reduce or better null standby power consumption. Indeed, while on standby, power management circuits are permanently active and consume unnecessary energy. This work presents an innovative technique based on RF wireless power transfer to null standby power consumption.

EPFL2022

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EPFL2022